Online commercial entities often engage in a variety of marketing strategies to increase conversion rates, which may be, for example, the percentage of visitors to a website of a online business that ultimately buy a product or service supplied via the website. One example of a popular marketing strategy employs market segmentation, in which a business may divide a group of potential customers, such as previous visitors to the website, into various subgroups according to their common purchasing characteristics or traits. The business may then tailor advertising, purchase offers, coupons, discounts, and the like to each identified consumer subgroup according to the perceived needs of that group in the hope that a greater number of people in each group will be motivated to purchase products or services from the business.
Typically, the business bases its market segmentation process on relatively static characteristics of each member of the overall customer group, such as, for example, age, gender, geographic location, marital status, number of children, income level, and the like. However, the use of such information often does not result in conversion rates significantly greater than what may be expected from randomly segmenting the potential customer group. Consequently, significant resources, such as money and employee time, that are typically invested in market segmentation using static customer characteristics may ultimately result in little-to-no positive economic return for the business entity.